Traffic-volume prediction device and method

US9240124B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-9240124-B2
Application numberUS-201214419512-A
CountryUS
Kind codeB2
Filing dateAug 8, 2012
Priority dateAug 8, 2012
Publication dateJan 19, 2016
Grant dateJan 19, 2016

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  5. First independent claim

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Abstract

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Because a route selection model for traffic demand prediction of selecting a route from among travel routes in probe data cannot include other routes than the travel route in the probe data, it is not possible to predict a traffic volume on the route that has not been traveled. A traffic-volume prediction device includes a simple-network creation device that makes a simple network connecting principal intersections extracted from travelling loci in the collected probe data, a model creation device that determines a utility between the principal intersections based on the data of the travelling loci and calculates a selection probability for each principal intersection based on the utility, and a traffic-volume assignment device that distributes a traffic volume to the routes between the principal intersections according to the selection probability and uses the traffic volume for each route candidate to be a traffic demand prediction object.

First claim

Opening claim text (preview).

The invention claimed is: 1. A traffic-volume prediction device that predicts a traffic volume between points using travelling locus data of a vehicle collected in advance, comprising: a network creation device that extracts principal intersections based on a proportion of a maximum ramification number to a number passing through a traveling locus between intersections on a travel route in the travelling locus data and creates a simple network connecting the principal intersections one another, a model creation device that calculates a utility of a route between the principal intersections based on a property value between the principal intersections and estimates a parameter of a route selection model for evaluating a selection probability at each principal intersection based on the utility, and a traffic-volume assignment device that calculates the selection probability of selecting the route between the principal intersections based on the estimated parameter of the route selection model and distributes the traffic volume to the route for predicting the traffic demand based on the selection probability. 2. The traffic-volume prediction device according to claim 1 , wherein the model creation device uses at least one of a travel time and a travel distance between the principal intersections obtained from the travelling locus data as the property value of the route between a principal intersection on the simple network and a plurality of principal intersections connected thereto. 3. The traffic-volume prediction device according to claim 1 , wherein the traffic-volume assignment device performs a simulation in which the same number of vehicles as the traffic volume assumed from the origin point to the destination point run on the simple network at random based on the selection probability of the principal intersection, and the quantity of vehicles running between the principal intersections is assumed as a predicted traffic volume between the principal intersection or between roads. 4. The traffic-volume prediction device according to claim 3 , wherein the traffic-volume prediction device obtains information including a site of occurrence of an event and influence of the site of occurrence on the traffic, and the traffic-volume assignment device updates the selection probability between a plurality of principal intersections by applying the influence on the traffic to the utility function for the principal intersections corresponding to the route passing through the site of occurrence of the event among the plurality of principal intersections, and distributes the traffic volume based on the updated selection probability. 5. A traffic-volume prediction method of predicting a traffic volume between points using travelling locus data of a vehicle collected in advance, comprising the steps of: network creation processing of extracting principal intersections based on a proportion of a maximum ramification number to a number passing through a traveling locus between intersections on a travel route in the travelling locus data and creating a simple network connecting the principal intersections one another, model creation processing of calculating a utility of a route between the principal intersections based on a property value between the principal intersections based on the travelling locus data and estimating a parameter of a route selection model for evaluating a selection probability at each principal intersection based on the utility, and traffic-volume assignment processing of calculating the selection probability of selecting the route between the principal intersections based on the parameter of the route selection model estimated at the model creation processing and distributing the traffic volume to the route for predicting the traffic demand based on the selection probability. 6. The traffic-volume prediction method according to claim 5 , wherein the model creation processing uses at least one of a travel time and a travel distance between the principal intersections obtained from the travelling locus data as the property value of the route between a principal intersection on the simple network and a plurality of principal intersections connected thereto. 7. The traffic-volume prediction method according to claim 5 , wherein the traffic-volume assignment processing performs a simulation in which the same number of vehicles as the traffic volume assumed from the origin point to the destination point run on the simple network at random based on the selection probability of the principal intersection, and assumes the quantity of vehicles running between the principal intersections as a predicted traffic volume between the principal intersection or between roads. 8. The traffic-volume prediction method according to claim 7 , wherein in the traffic-volume prediction method, information is obtained including a site of occurrence of an event and influence of the site of occurrence to the traffic, and the traffic-volume assignment processing updates the selection probability between a plurality of principal intersections by applying the influence on the traffic to the utility function for the principal intersections corresponding to the route passing through the site of occurrence of the event among the plurality of principal intersections, and distributes the traffic volume based on the updated selection probability.

Assignees

Inventors

Classifications

  • G08G1/0129Primary

    for creating historical data or processing based on historical data · CPC title

  • from the vehicle, e.g. floating car data [FCD] · CPC title

  • for traffic information dissemination · CPC title

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Frequently asked questions

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What does patent US9240124B2 cover?
Because a route selection model for traffic demand prediction of selecting a route from among travel routes in probe data cannot include other routes than the travel route in the probe data, it is not possible to predict a traffic volume on the route that has not been traveled. A traffic-volume prediction device includes a simple-network creation device that makes a simple network connecting pr…
Who is the assignee on this patent?
Hiruta Tomoaki, Kato Manabu, Okude Mariko, and 1 more
What technology area does this patent fall under?
Primary CPC classification G08G1/0129. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Jan 19 2016 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).